Ian Osband

According to our database, Ian Osband authored at least 40 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping.

Vikranth Dwaracherla, Zheng Wen, Ian Osband, Xiuyuan Lu, Seyed Mohammad Asghari, Benjamin Van Roy

Trans. Mach. Learn. Res., 2023

Reinforcement Learning, Bit by Bit.

Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen

Found. Trends Mach. Learn., 2023

Approximate Thompson Sampling via Epistemic Neural Networks.

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Epistemic Neural Networks.

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Fine-Tuning Language Models via Epistemic Neural Networks.

Ian Osband, Seyed Mohammad Asghari, Benjamin Van Roy, Nat McAleese, John Aslanides, Geoffrey Irving

CoRR, 2022

Robustness of Epinets against Distributional Shifts.

Xiuyuan Lu, Ian Osband, Seyed Mohammad Asghari, Sven Gowal, Vikranth Dwaracherla, Zheng Wen, Benjamin Van Roy

CoRR, 2022

Evaluating high-order predictive distributions in deep learning.

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy

Proceedings of the Uncertainty in Artificial Intelligence, 2022

The Neural Testbed: Evaluating Joint Predictions.

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Dieterich Lawson, Botao Hao, Brendan O'Donoghue, Benjamin Van Roy

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Botao Hao, Morteza Ibrahimi, Dieterich Lawson, Xiuyuan Lu, Brendan O'Donoghue, Benjamin Van Roy

CoRR, 2021

Evaluating Probabilistic Inference in Deep Learning: Beyond Marginal Predictions.

Xiuyuan Lu, Ian Osband, Benjamin Van Roy, Zheng Wen

CoRR, 2021

Epistemic Neural Networks.

Ian Osband, Zheng Wen, Mohammad Asghari, Morteza Ibrahimi, Xiyuan Lu, Benjamin Van Roy

CoRR, 2021

Matrix games with bandit feedback.

Brendan O'Donoghue, Tor Lattimore, Ian Osband

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Stochastic matrix games with bandit feedback.

Brendan O'Donoghue, Tor Lattimore, Ian Osband

CoRR, 2020

Behaviour Suite for Reinforcement Learning.

Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvári, Satinder Singh, Benjamin Van Roy, Richard S. Sutton, David Silver, Hado van Hasselt

Proceedings of the 8th International Conference on Learning Representations, 2020

Making Sense of Reinforcement Learning and Probabilistic Inference.

Brendan O'Donoghue, Ian Osband, Catalin Ionescu

Proceedings of the 8th International Conference on Learning Representations, 2020

Hypermodels for Exploration.

Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Ian Osband, Zheng Wen, Benjamin Van Roy

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Deep Exploration via Randomized Value Functions.

Ian Osband, Benjamin Van Roy, Daniel J. Russo, Zheng Wen

J. Mach. Learn. Res., 2019

Meta-learning of Sequential Strategies.

Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alexander Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin J. Miller, Mohammad Gheshlaghi Azar, Ian Osband, Neil C. Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew M. Botvinick, Shane Legg

CoRR, 2019

2018

A Tutorial on Thompson Sampling.

Daniel Russo, Benjamin Van Roy, Abbas Kazerouni, Ian Osband, Zheng Wen

Found. Trends Mach. Learn., 2018

Randomized Prior Functions for Deep Reinforcement Learning.

Ian Osband, John Aslanides, Albin Cassirer

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Scalable Coordinated Exploration in Concurrent Reinforcement Learning.

Maria Dimakopoulou, Ian Osband, Benjamin Van Roy

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

The Uncertainty Bellman Equation and Exploration.

Brendan O'Donoghue, Ian Osband, Rémi Munos, Volodymyr Mnih

Proceedings of the 35th International Conference on Machine Learning, 2018

Noisy Networks For Exploration.

Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Matteo Hessel, Ian Osband, Alex Graves, Volodymyr Mnih, Rémi Munos, Demis Hassabis, Olivier Pietquin, Charles Blundell, Shane Legg

Proceedings of the 6th International Conference on Learning Representations, 2018

Deep Q-learning From Demonstrations.

Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Ian Osband, Gabriel Dulac-Arnold, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

On Optimistic versus Randomized Exploration in Reinforcement Learning.

Ian Osband, Benjamin Van Roy

CoRR, 2017

Gaussian-Dirichlet Posterior Dominance in Sequential Learning.

Ian Osband, Benjamin Van Roy

CoRR, 2017

Learning from Demonstrations for Real World Reinforcement Learning.

Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Andrew Sendonaris, Gabriel Dulac-Arnold, Ian Osband, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys

CoRR, 2017

Noisy Networks for Exploration.

Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Ian Osband, Alex Graves, Vlad Mnih, Rémi Munos, Demis Hassabis, Olivier Pietquin, Charles Blundell, Shane Legg

CoRR, 2017

A Tutorial on Thompson Sampling.

Daniel Russo, Benjamin Van Roy, Abbas Kazerouni, Ian Osband

CoRR, 2017

Why is Posterior Sampling Better than Optimism for Reinforcement Learning?

Ian Osband, Benjamin Van Roy

Proceedings of the 34th International Conference on Machine Learning, 2017

Minimax Regret Bounds for Reinforcement Learning.

Mohammad Gheshlaghi Azar, Ian Osband, Rémi Munos

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

On Lower Bounds for Regret in Reinforcement Learning.

Ian Osband, Benjamin Van Roy

CoRR, 2016

Posterior Sampling for Reinforcement Learning Without Episodes.

Ian Osband, Benjamin Van Roy

CoRR, 2016

Deep Exploration via Bootstrapped DQN.

Ian Osband, Charles Blundell, Alexander Pritzel, Benjamin Van Roy

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Generalization and Exploration via Randomized Value Functions.

Ian Osband, Benjamin Van Roy, Zheng Wen

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Bootstrapped Thompson Sampling and Deep Exploration.

Ian Osband, Benjamin Van Roy

CoRR, 2015

2014

Near-optimal Regret Bounds for Reinforcement Learning in Factored MDPs.

Ian Osband, Benjamin Van Roy

CoRR, 2014

Model-based Reinforcement Learning and the Eluder Dimension.

Ian Osband, Benjamin Van Roy

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Near-optimal Reinforcement Learning in Factored MDPs.

Ian Osband, Benjamin Van Roy

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

(More) Efficient Reinforcement Learning via Posterior Sampling.

Ian Osband, Daniel Russo, Benjamin Van Roy

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013